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Model-Driven Risk Analysis: The CORAS Approach
by Ketil Stølen Bjørnar Solhaug Mass Soldal LundThe term "risk" is known from many fields, and we are used to references to contractual risk, economic risk, operational risk, legal risk, security risk, and so forth. We conduct risk analysis, using either offensive or defensive approaches to identify and assess risk. Offensive approaches are concerned with balancing potential gain against risk of investment loss, while defensive approaches are concerned with protecting assets that already exist. In this book, Lund, Solhaug and Stølen focus on defensive risk analysis, and more explicitly on a particular approach called CORAS. CORAS is a model-driven method for defensive risk analysis featuring a tool-supported modelling language specially designed to model risks. Their book serves as an introduction to risk analysis in general, including the central concepts and notions in risk analysis and their relations. The authors' aim is to support risk analysts in conducting structured and stepwise risk analysis. To this end, the book is divided into three main parts. Part I of the book introduces and demonstrates the central concepts and notation used in CORAS, and is largely example-driven. Part II gives a thorough description of the CORAS method and modelling language. After having completed this part of the book, the reader should know enough to use the method in practice. Finally, Part III addresses issues that require special attention and treatment, but still are often encountered in real-life risk analysis and for which CORAS offers helpful advice and assistance. This part also includes a short presentation of the CORAS tool support. The main target groups of the book are IT practitioners and students at graduate or undergraduate level. They will appreciate a concise introduction into the emerging field of risk analysis, supported by a sound methodology, and completed with numerous examples and detailed guidelines.
Model: The Ugly Business of Beautiful Women
by Michael GrossInvestigative journalist Michael Gross delves into the history of models and takes us into the private studios and hidden villas where models play and are preyed upon, going beyond modeling’s carefully constructed facade of glamour to expose the scandal and untold truths that permeate the seemingly glamorous business.Here for the first time is the complete story of the international model business—and its evil twin: legalized flesh peddling. It’s a tale of vast sums of money, rape both symbolic and of the flesh, sex and drugs, obsession and tragic death. At its heart is the most unholy combination in commerce: beautiful, young women and rich, lascivious men.Fashion insider Michael Gross has interviewed modeling’s pioneers, survivors, and hangers–on, and he tells the story of the greats: Lisa Fonssagrives; Anita Colby, Candy Jones; Dorian Leigh and her sister Suzy Parker; Jean Shrimpton and Twiggy; Veruschka and Lauren Hutton; and today’s supermodel trinity, Christy, Naomi and Linda.
Modeling Applications in the Airline Industry
by Ahmed Abdelghany Khaled AbdelghanyModeling Applications in the Airline Industry explains the different functions and tactics performed by airlines during their planning and operation phases. Each function receives a full explanation of the challenges it brings and a solution methodology is presented, supported by numerical illustrative examples wherever possible. The book also highlights the main limitations of current practice and provides a brief description of future work related to each function. The authors have filtered the rich literature of airline management to include only the research that has actually been adopted by the airlines, giving a genuinely accurate representation of real airline management and its continuing development of solution methodologies. The book consists of 20 chapters divided into 4 sections: - Demand Modeling and Forecasting - Scheduling of Resources - Revenue Management - Irregular Operations Management. The book will be a valuable source or a handbook for individuals seeking a career in airline management. Written by experts with significant working experience within the industry, it offers readers insights to the real practice of operations modelling. In particular the book makes accessible the complexities of the key airline functions and explains the interrelation between them.
Modeling Complex Linguistic Information to Support Group Decision Making Under Uncertainty: Theories, Methods and Applications (Uncertainty and Operations Research)
by Zhen Zhang Wenyu Yu Zhuolin LiThis book systematically explores theories related to linguistic computational models and group decision making methods under uncertainty. It introduces innovative linguistic computational models capable of fusing complex linguistic information, including multi-granular linguistic information, unbalanced linguistic information and hesitant fuzzy linguistic information. Building upon the linguistic computational models, this book presents methods tailored to various types of group decision making problems under uncertainty. Additionally, it delves into group decision making problems where the personalized individual semantics of experts are considered. The book also showcases practical applications of the proposed group decision making methods, ranging from ERP system supplier selection to talent recruitment, subway line selection, and location selection for electric vehicle charging stations. By shedding light on novel models for modeling complex linguistic information and introducing new approaches to addressing linguistic group decision making challenges, this book offers valuable insights for engineers, researchers, and postgraduates interested in decision analysis, operations research, computational intelligence, management science and engineering, and related fields.
Modeling Discrete Competitive Facility Location
by Athanasia KarakitsiouThis book presents an up-to-date review of modeling and optimization approaches for location problems along with a new bi-level programming methodology which captures the effect of competition of both producers and customers on facility location decisions. While many optimization approaches simplify location problems by assuming decision making in isolation, this monograph focuses on models which take into account the competitive environment in which such decisions are made. New insights in modeling, algorithmic and theoretical possibilities are opened by this approach and new applications are possible. Competition on equal term plus competition between market leader and followers are considered in this study, consequently bi-level optimization methodology is emphasized and further developed. This book provides insights regarding modeling complexity and algorithmic approaches to discrete competitive location problems. In traditional location modeling, assignment of customer demands to supply sources are made for which the associated costs target the firm and not the customers, though in many real world situations the cost is incurred by the customers. Moreover, there may be customer competition for the provided services. Thus, a new methodological framework is needed in order to encompass such considerations into the modeling and solution process. This book offers initial directions for further research and development along these lines. Aimed toward graduate students and researchers in the field of mathematics, computer science, operational research and game theory, this title provides necessary information on which further research contributions can be based.
Modeling Dynamic Economic Systems
by Bruce Hannon Matthias RuthThis book explores the dynamic processes in economic systems, concentrating on the extraction and use of the natural resources required to meet economic needs. Sections cover methods for dynamic modeling in economics, microeconomic models of firms, modeling optimal use of both nonrenewable and renewable resources, and chaos in economic models. This book does not require a substantial background in mathematics or computer science.
Modeling Economic Instability: A History of Early Macroeconomics (Springer Studies in the History of Economic Thought)
by Michaël Assous Vincent CarretThis book offers a fresh perspective on the early history of macroeconomics, by examining the macro-dynamic models developed from the late 1920s to the late 1940s, and their treatment of economic instability. It first explores the differences and similarities between the early mathematical business cycle models developed by Ragnar Frisch, Michal Kalecki, Jan Tinbergen and others, which were presented at meetings of the Econometric Society and discussed in private correspondence. By doing so, it demonstrates the diversity of models representing economic phenomena and especially economic crises and instability. Jan Tinbergen emerged as one of the most original and pivotal economists of this period, before becoming a leader of the macro-econometric movement, a role for which he is better known. His emphasis on economic policy was later mirrored in the United States in Paul Samuelson’s early work on business cycles analysis, which, drawing on Alvin Hansen, aimed at interpreting the 1937-1938 recession. The authors then show that the subsequent shift in Samuelson's approach, from the study of business cycle trajectories to the comparison of equilibrium points, provided a response to the econometricians' critique of early Keynesian models. In the early 1940s, Samuelson was able to link together the tools that had been developed by the econometricians and the economic content that was at the heart of the so-called Keynesian revolution. The problem then shifted from business cycle trajectories to the disequilibrium between economic aggregates, and the issues raised by the global stability of full employment equilibrium. This was addressed by Oskar Lange, who presented an analysis of market coordination failures, and Lawrence Klein, Samuelson's first PhD student, who pursued empirical work in this direction. The book highlights the various visions and approaches that were embedded in these macro-dynamic models, and that their originality is of interest to today's model builders as well as to students and anyone interested in how new economic ideas come to be developed.
Modeling Energy-Economy Interactions: Five Appoaches (Routledge Revivals)
by Charles J. HitchThis report, first published in 1977, explores several different approaches to the same question; namely, how severe will be the impact on key U.S. macro-economic variables of the transition from main reliance on oil and natural gas to other sources of energy? This book will be of interest to students of economics and environmental studies.
Modeling Environment-Improving Technological Innovations under Uncertainty (Routledge Explorations in Environmental Economics)
by Anil Markandya Alexander A. GolubThe issues of technology and uncertainty are very much at the heart of the policy debate of how much to control greenhouse gas emissions. The costs of doing so are present and high while the benefits are very much in the future and, most importantly, they are highly uncertain. Whilst there is broad consensus on the key elements of climate change science and agreement that near-term actions are needed to prevent dangerous anthropogenic interference with the climate system, there is little agreement on the costs and benefits of climate policy. The book looks at different ways of reconciling the needs for sustainability and equity with the costs of action now. Presenting a compendium of methodologies for evaluating the economic impact of technological innovation upon climate-change policy, this book describes mathematical models and their predictions. The goal is to provide a practitioner’s guide for doing the science of economics and climate change. Because the assumptions motivating different problems in the economics of climate change have different complexities, a number of models are presented with varying levels of difficulty: reduced-form and structural, partial- and general-equilibrium, closed-form and computational. A unifying theme of these models is the incorporation of a number of price and quantity instruments and an analysis of their respective efficacies. This book presents models that contain structural uncertainty, i.e., uncertainty that economic agents respond to via their risk attitudes. The novelty of this book is to relate the effects of risk and risk attitudes to environment-improving technological innovation.
Modeling Markets
by Peter S. H. Leeflang Jaap E. Wieringa Tammo H. A. Bijmolt Koen H. PauwelsThis book is about how models can be developed to represent demand and supply on markets, where the emphasis is on demand models. Its primary focus is on models that can be used by managers to support marketing decisions. The market environment is changing rapidly and constantly. Prior to the introduction of scanner equipment in retail outlets, ACNielsen, the major supplier of information on brand performance, claimed that its business was to provide the score but not to explain or predict it. With technological advances and the introduction of the Internet, the opportunity to obtain meaningful estimates of demand functions has vastly improved; models that provide information about the sensitivity of market behavior to marketing activities such as advertising, pricing, promotions and distribution are now routinely used by managers for the identification of changes in marketing programs that can improve brand performance. In today's environment of information overload, the challenge is to make sense of the data that is being provided globally, in real time, from thousands of sources. Modeling Markets presents a comprehensive overview of the tools and methodologies that managers can use in decision making. It has long been known that even simple models outperform judgments in predicting outcomes in a wide variety of contexts. More complex models potentially provide insights about structural relations not available from casual observations. Although marketing models are now widely accepted, the quality of the marketing decisions is critically dependent upon the quality of the models on which those decisions are based. In this book, the authors present a wealth of insights developed at the forefront of the field, covering all key aspects of specification, estimation, validation and use of models. The most current insights and innovations in quantitative marketing are presented, including in-depth discussion of Bayesian estimation methods. Throughout the book, the authors provide examples and illustrations. This book will be of interest to researchers, analysts, managers and students who want to understand, develop or use models of marketing phenomena.
Modeling Monetary Economies
by Scott Freeman Bruce Champ Joseph HaslagThe approach of this text is to teach monetary economics using the classical paradigm of rational agents in a market setting. Too often monetary economics has been taught as a collection of facts about existing institutions for students to memorize. By teaching from first principles instead, the authors aim to instruct students not only in the monetary policies and institutions that exist today in the United States and Canada, but also in what policies and institutions may or should exist tomorrow and elsewhere. The text builds on a simple, clear monetary model and applies this framework consistently to a wide variety of monetary questions. The authors have added in this third edition new material on money as a means of replacing imperfect social record keeping, the role of currency in banking panics, and a description of the policies implemented to deal with the banking crises that began in 2007.
Modeling Risk Management for Resources and Environment in China
by Desheng Dash Wu Yong ZhouThis edited volume expands the scope of risk management beyond finance to include resources and environment issues in China. It presents the state-of-the-art approaches of using risk management to effectively manage resources and environment. Both case studies and theoretical methodologies are discussed.
Modeling Risk Management in Sustainable Construction
by Desheng Dash WuIn this edited volume, we present the state-of-the-art views of the perspective of enterprise risk management, to include frameworks and controls in the ERM process with respect to supply chains, constructions, and project, energy, environmental and sustainable development risk management. The bulk of this volume is devoted to presenting a number of modeling approaches that have been (or could be) applied to enterprise risk management in construction.
Modeling Software Behavior: A Craftsman's Approach
by Paul C. JorgensenThis book provides engineers, developers, and technicians with a detailed treatment of various models of software behavior that will support early analysis, comprehension, and model-based testing. The expressive capabilities and limitations of each behavioral model are also discussed.
Modeling Structural Change in the U.S. Textile Industry (Studies on Industrial Productivity: Selected Works)
by Shu Yang Barry K. GoodwinFirst Published in 2000. Routledge is an imprint of Taylor & Francis, an informa company.
Modeling Structured Finance Cash Flows with MicrosoftExcel
by Allman Keith A.A practical guide to building fully operational financial cash flow models for structured finance transactions Structured finance and securitization deals are becoming more commonplace on Wall Street. Up until now, however, market participants have had to create their own models to analyze these deals, and new entrants have had to learn as they go. Modeling Structured Finance Cash Flows with Microsoft Excel provides readers with the information they need to build a cash flow model for structured finance and securitization deals. Financial professional Keith Allman explains individual functions and formulas, while also explaining the theory behind the spreadsheets. Each chapter begins with a discussion of theory, followed by a section called "Model Builder," in which Allman translates the theory into functions and formulas. In addition, the companion CD-ROM features all of the modeling exercises, as well as a final version of the model that is created in the text. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
Modeling a New Computer Framework for Managing Healthcare Organizations: Balancing and Optimizing Patient Satisfaction, Owner Satisfaction, and Medical Resources
by Soraia OueidaThe medical sector has been growing exponentially over the last decade and healthcare services are becoming more complex and costly. In order to continue efficiently and effectively managing patient safety, quality, and the effectiveness of the healthcare systems, new methodologies are needed. This book provides a platform to address this growing need and to improve practice. With the introduction of a new computer platform package for the management of medical organizations and healthcare systems, Modeling a New Computer Framework for Managing Healthcare Organizations aims to improve management techniques and increase overall satisfaction scores of patients, owners, and medical resources. The platform outlined will improve the daily operation of a healthcare system, focusing on the emergency department, and can be used to study the operation flow of a unit for performance optimization. It offers a user-friendly interface and proposed programming language, along with a visual and simple practice to collect and understand statistical outputs. Essential reading for decision makers on different levels in the healthcare organization hierarchy, this book can also be used by management to improve the performance of the organization and decision makers to hire resources, enhance workflows or both. It guides designers and system implementers in a step-by-step approach to make optimal decisions for resource allocation and helps designers and management to detect deficiencies in ongoing processes and fix or enhance them. Soraia Oueida is an instructor in the Department of Computer Engineering at the American University of the Middle East. She is an IEEE member and her research interests include Simulation Modeling, Discrete Mathematics, Petri Net, Workflows, Blockchain, IoT, Industrial Management Systems.
Modeling and Analysis of Stochastic Systems (Chapman & Hall/CRC Texts in Statistical Science)
by Vidyadhar G. KulkarniBuilding on the author’s more than 35 years of teaching experience, Modeling and Analysis of Stochastic Systems, Third Edition, covers the most important classes of stochastic processes used in the modeling of diverse systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. The third edition has been updated with several new applications, including the Google search algorithm in discrete time Markov chains, several examples from health care and finance in continuous time Markov chains, and square root staffing rule in Queuing models. More than 50 new exercises have been added to enhance its use as a course text or for self-study. The sequence of chapters and exercises has been maintained between editions, to enable those now teaching from the second edition to use the third edition. Rather than offer special tricks that work in specific problems, this book provides thorough coverage of general tools that enable the solution and analysis of stochastic models. After mastering the material in the text, readers will be well-equipped to build and analyze useful stochastic models for real-life situations.
Modeling and Forecasting Primary Commodity Prices
by Walter C. LabysRecent economic growth in China and other Asian countries has led to increased commodity demand which has caused price rises and accompanying price fluctuations not only for crude oil but also for the many other raw materials. Such trends mean that world commodity markets are once again under intense scrutiny. This book provides new insights into the modeling and forecasting of primary commodity prices by featuring comprehensive applications of the most recent methods of statistical time series analysis. The latter utilize econometric methods concerned with structural breaks, unobserved components, chaotic discovery, long memory, heteroskedasticity, wavelet estimation and fractional integration. Relevant tests employed include neural networks, correlation dimensions, Lyapunov exponents, fractional integration and rescaled range. The price forecasting involves structural time series trend plus cycle and cyclical trend models. Practical applications focus on the price behaviour of more than twenty international commodity markets.
Modeling and Optimization in Green Logistics
by Patrick Siarry Bassem Jarboui Houda DerbelThis book presents recent work that analyzes general issues of green logistics and smart cities. The contributed chapters consider operating models with important ecological, economic, and social objectives.The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.
Modeling and Optimization in Space Engineering: State of the Art and New Challenges (Springer Optimization and Its Applications #144)
by Giorgio Fasano János D. PintérThis book presents advanced case studies that address a range of important issues arising in space engineering. An overview of challenging operational scenarios is presented, with an in-depth exposition of related mathematical modeling, algorithmic and numerical solution aspects. The model development and optimization approaches discussed in the book can be extended also towards other application areas. The topics discussed illustrate current research trends and challenges in space engineering as summarized by the following list: • Next Generation Gravity Missions • Continuous-Thrust Trajectories by Evolutionary Neurocontrol • Nonparametric Importance Sampling for Launcher Stage Fallout • Dynamic System Control Dispatch • Optimal Launch Date of Interplanetary Missions • Optimal Topological Design • Evidence-Based Robust Optimization • Interplanetary Trajectory Design by Machine Learning • Real-Time Optimal Control • Optimal Finite Thrust Orbital Transfers • Planning and Scheduling of Multiple Satellite Missions • Trajectory Performance Analysis • Ascent Trajectory and Guidance Optimization • Small Satellite Attitude Determination and Control • Optimized Packings in Space Engineering • Time-Optimal Transfers of All-Electric GEO Satellites Researchers working on space engineering applications will find this work a valuable, practical source of information. Academics, graduate and post-graduate students working in aerospace, engineering, applied mathematics, operations research, and optimal control will find useful information regarding model development and solution techniques, in conjunction with real-world applications.
Modeling and Optimization: Theory and Applications
by Tamás Terlaky Martin TakáčThis volume contains a selection of contributions that were presented at the Modeling and Optimization: Theory and Applications Conference (MOPTA) held at Lehigh University in Bethlehem, Pennsylvania, USA on August 17-19, 2016. The conference brought together a diverse group of researchers and practitioners, working on both theoretical and practical aspects of continuous or discrete optimization. Topics presented included algorithms for solving convex, network, mixed-integer, nonlinear, and global optimization problems, and addressed the application of deterministic and stochastic optimization techniques in energy, finance, logistics, analytics, health, and other important fields. The contributions contained in this volume represent a sample of these topics and applications and illustrate the broad diversity of ideas discussed at the meeting.
Modeling and Simulating Complex Business Perceptions: Using Graphical Models and Fuzzy Cognitive Maps (Fuzzy Management Methods)
by Zoumpolia DikopoulouFuzzy cognitive maps (FCMs) have gained popularity in the scientific community due to their capabilities in modeling and decision making for complex problems.This book presents a novel algorithm called glassoFCM to enable automatic learning of FCM models from data. Specifically, glassoFCM is a combination of two methods, glasso (a technique originated from machine learning) for data modeling and FCM simulation for decision making. The book outlines that glassoFCM elaborates simple, accurate, and more stable models that are easy to interpret and offer meaningful decisions. The research results presented are based on an investigation related to a real-world business intelligence problem to evaluate characteristics that influence employee work readiness.Finally, this book provides readers with a step-by-step guide of the 'fcm' package to execute and visualize their policies and decisions through the FCM simulation process.
Modeling and Simulation Based Analysis in Reliability Engineering (Advanced Research in Reliability and System Assurance Engineering)
by Mangey RamRecent developments in reliability engineering has become the most challenging and demanding area of research. Modeling and Simulation, along with System Reliability Engineering has become a greater issue because of high-tech industrial processes, using more complex systems today. This book gives the latest research advances in the field of modeling and simulation, based on analysis in engineering sciences. Features Focuses on the latest research in modeling and simulation based analysis in reliability engineering. Covers performance evaluation of complex engineering systems Identifies and fills the gaps of knowledge pertaining to engineering applications Provides insights on an international and transnational scale Modeling and Simulation Based Analysis in Reliability Engineering aims at providing a reference for applications of mathematics in engineering, offering a theoretical sound background with adequate case studies, and will be of interest to researchers, practitioners, and academics.
Modeling and Valuation of Energy Structures: Analytics, Econometrics, and Numerics (Applied Quantitative Finance)
by Daniel MahoneyCommodity markets present several challenges for quantitative modeling. These include high volatilities, small sample data sets, and physical, operational complexity. In addition, the set of traded products in commodity markets is more limited than in financial or equity markets, making value extraction through trading more difficult. These facts make it very easy for modeling efforts to run into serious problems, as many models are very sensitive to noise and hence can easily fail in practice. Modeling and Valuation of Energy Structures is a comprehensive guide to quantitative and statistical approaches that have been successfully employed in support of trading operations, reflecting the author's 17 years of experience as a front-office 'quant'. The major theme of the book is that simpler is usually better, a message that is drawn out through the reality of incomplete markets, small samples, and informational constraints. The necessary mathematical tools for understanding these issues are thoroughly developed, with many techniques (analytical, econometric, and numerical) collected in a single volume for the first time. A particular emphasis is placed on the central role that the underlying market resolution plays in valuation. Examples are provided to illustrate that robust, approximate valuations are to be preferred to overly ambitious attempts at detailed qualitative modeling.